scholarly journals Various Image Processing Attacks for Image Watermarking in the Wavelet Domain Using Singular Value Decomposition and Discrete Cosine Transform

2021 ◽  
Vol 8 (2) ◽  
pp. 51-59
Author(s):  
Riyajuddin ◽  
Arikera Padmanabha Reddy

The dispersal of digital media due to the fast evolution of networked multimedia systems has created an essential need for copyright prompting technologies that can protect multimedia objects such as text, images, audio and videos from copyright ownership. This paper proposes digital image watermarking algorithm for copyright protection based on discrete wavelet transform, discrete cosine transform and singular value decomposition. In this method a watermark is embedded into the low frequency sub-band of a host image, after subjecting the watermarked image to various attacks like Gaussian noise, rotation sharpening, noise and pepper salt and speckle noise etc., we extract the originally inserted watermark images from LL sub-band by Truncated singular value decomposition and compare them on the basis of their mean square error, peak signal to noise ratio and normalized correlation values. Experimental results are provided to illustrate that the proposed scheme is the robustness of the technique on wide set of attacks.

Author(s):  
Rahul Dixit ◽  
Amita Nandal ◽  
Arvind Dhaka ◽  
Vardan Agarwal ◽  
Yohan Varghese

Background: Nowadays information security is one of the biggest issues of social networks. The multimedia data can be tampered with, and the attackers can then claim its ownership. Image watermarking is a technique that is used for copyright protection and authentication of multimedia. Objective: We aim to create a new and more robust image watermarking technique to prevent illegal copying, editing and distribution of media. Method : The watermarking technique proposed in this paper is non-blind and employs Lifting Wavelet Transform on the cover image to decompose the image into four coefficient matrices. Then Discrete Cosine Transform is applied which separates a selected coefficient matrix into different frequencies and later Singular Value Decomposition is applied. Singular Value Decomposition is also applied to the watermarking image and it is added to the singular matrix of the cover image which is then normalized followed by the inverse Singular Value Decomposition, inverse Discrete Cosine Transform and inverse Lifting Wavelet Transform respectively to obtain an embedded image. Normalization is proposed as an alternative to the traditional scaling factor. Results: Our technique is tested against attacks like rotation, resizing, cropping, noise addition and filtering. The performance comparison is evaluated based on Peak Signal to Noise Ratio, Structural Similarity Index Measure, and Normalized Cross-Correlation. Conclusion: The experimental results prove that the proposed method performs better than other state-of-the-art techniques and can be used to protect multimedia ownership.


Author(s):  
Rahul Dixit ◽  
Amita Nandal ◽  
Arvind Dhaka ◽  
Yohan Varghese ◽  
Vardan Agarwal

: Watermarking is a process of embedding a message inside a digital signal like an image, video or text. It is used for several key reasons such as authenticity verification, ownership recognition and hidden communication. In this paper, we discuss about image watermarking, where secret messages are stored in images. Introduction: We propose a dual watermarking approach, which is based on Discrete Cosine Transform, Discrete Wavelet Transform and Singular Value Decomposition methods. This paper considers one watermark as robust and other water mark as fragile. Method: The robust watermark is embedded in Discrete Wavelet Transform- Singular Value Decomposition - domain and is used to transmit hidden messages. The fragile watermark is embedded in Discrete Cosine Transform domain and is used for verification of secret message of the robust watermark. The proposed algorithm is tested in the experimental results section and shows promising results against denoising, rotation, translation and cropping attacks. Result: The results show that the performance of the proposed algorithm in terms of mean squared error, structural similarity and peak signal to noise ratio is S4considerable as compared with the existing methods. Discussion: We present the comparison results with Himanshu et. al. in table 10, from which we can see that our method performs better with gaussian noise and rotational attack only lacking with Salt and Pepper noise. Fig. 7 and Fig. 8, in terms of resulting PSNR shows the variation of noise variance and degree of rotation. From the graphs it is evident that out method performs better against Gaussian and rotational attack. Conclusion: In this paper a dual watermarking method is proposed in which one watermark is fragile which is called as authentication watermark whereas the other watermark is robust and is called as the information watermark. The authentication watermark is embedded in the fractional part of DCT domain in the cover image and the information watermark is embedded in the diagonal vector of the LL sub-band.


2017 ◽  
Vol 4 (6) ◽  
pp. 170326 ◽  
Author(s):  
Soumitra Roy ◽  
Arup Kumar Pal

Digital image watermarking has emerged as a promising solution for copyright protection. In this paper, a discrete cosine transform (DCT) and singular value decomposition (SVD) based hybrid robust image watermarking method using Arnold scrambling is proposed and simulated to protect the copyright of natural images. In this proposed scheme, before embedding, watermark is scrambled with Arnold scrambling. Then, the greyscale cover image and encrypted watermark logo are decomposed into non-overlapping blocks and subsequently some selected image blocks are transformed into the DCT domain for inserting the watermark blocks permanently. For better imperceptibility and effectiveness, in this proposed algorithm, watermark image blocks are embedded into singular values of selected blocks by multiplying with a feasible scaling factor. Simulation result demonstrates that robustness is achieved by recovering satisfactory watermark data from the reconstructed cover image after applying common geometric transformation attacks (such as rotation, flip operation, cropping, scaling, shearing and deletion of lines or columns operation), common enhancement technique attacks (such as low-pass filtering, histogram equalization, sharpening, gamma correction, noise addition) and jpeg compression attacks.


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